The goal of HOTspots is to display the data about antimmicrobial resistance in the Top End in a way that is easy to understand and useable for the audience. The audience nicludes members of the public, medical professionals and policy/decision makers.

Outline of the project

Content

  • Patterns of drug resistance in space and time
  • Rural and regional areas
  • Local rates

Audience

  • Local stakeholder
  • Prescribers and doctors
  • Policy and guideline makers

Adjectives

  • user friendly
  • Sophistocated

The Specifications from Teresa

General

  • navigation bar
    • Opening page as heat map
    • region and age plots
    • methodology
    • reports
    • links and news
    • Terms of use, data disclaimer
    • data
    • options to share

Heat map

  • statistical area three
  • grey out options of microbe/antimicrobe that dont exist or we have no data on

Plots and tables

  • region and age plots

Download report

  • pdf
  • including summary statistics, plots, antibiogram

Options to add later

Other options that might be important or interesting - age - social disadvantage - remoteness index - household structure - gender - international areas

The data

The data is supplied by the HOTspots team; currently the member that supplies the data is Will Cunningham. The data is saved to a dropbox folder which is shared with Alys Young. The data is comprised of 2 csv files; HOTspots_yearly_age&sex.csv and HOTspots_monthly.csv. The HOTspots_yearly_age&sex.csv file contains annual antimicrobial resistance data split for each age and sex category. The HOTspots_monthly.csv file contains monthly resistance data.

## The raw data

## Monthly
hotspot_data <-  read.csv("www/data/HOTspots_monthly.csv")
hotspot_data$date_dmy <- as.Date(paste("01", hotspot_data$month_year), format = "%d %b %y")
head(hotspot_data)
#>   source jurisdiction                region sample_type     onset     organism
#> 1  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 2  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 3  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 4  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 5  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 6  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#>   antimicrobial year month_year num_of_tests_monthly_raw resistant_monthly_raw
#> 1      Amikacin 2008     Mar 08                        1                     0
#> 2      Amikacin 2009     May 09                        1                     0
#> 3      Amikacin 2010     May 10                        1                     0
#> 4      Amikacin 2010     Aug 10                        1                     0
#> 5      Amikacin 2010     Sep 10                        1                     0
#> 6      Amikacin 2010     Nov 10                        1                     0
#>   susceptible_monthly_raw percent_resistant_monthly_raw   date_dmy
#> 1                       1                             0 2008-03-01
#> 2                       1                             0 2009-05-01
#> 3                       1                             0 2010-05-01
#> 4                       1                             0 2010-08-01
#> 5                       1                             0 2010-09-01
#> 6                       1                             0 2010-11-01

## Yearly
hotspot_yearly_data_full <-  read.csv("www/data/HOTspots_yearly_age&sex.csv")
head(hotspot_yearly_data_full)
#>   source jurisdiction                region sample_type     onset     organism
#> 1  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 2  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 3  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 4  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 5  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#> 6  Human          FNQ Cairns and Hinterland         All Community A. baumannii
#>   antimicrobial year age_group sex num_of_tests_yearly_raw resistant_yearly_raw
#> 1      Amikacin 2008     61-80   F                       1                    0
#> 2      Amikacin 2009     26-40   F                       1                    0
#> 3      Amikacin 2010      6-15   F                       1                    0
#> 4      Amikacin 2010     16-25   F                       1                    0
#> 5      Amikacin 2010     26-40   F                       1                    0
#> 6      Amikacin 2010     41-60   F                       1                    0
#>   susceptible_yearly_raw percent_resistant_yearly_raw num_of_tests_yearly
#> 1                      1                            0                  NA
#> 2                      1                            0                  NA
#> 3                      1                            0                  NA
#> 4                      1                            0                  NA
#> 5                      1                            0                  NA
#> 6                      1                            0                  NA
#>   resistant_yearly susceptible_yearly percent_resistant_yearly
#> 1               NA                 NA                       NA
#> 2               NA                 NA                       NA
#> 3               NA                 NA                       NA
#> 4               NA                 NA                       NA
#> 5               NA                 NA                       NA
#> 6               NA                 NA                       NA

The HOTspots_yearly_age&sex.csv file is cleaned in the Data_manipulation.R script to create 4 files, 3 of which are loaded for the shiny app. Cleaning includes removing NAs and duplicates, and aggregating across superfluous groups.

hotspot_yearly_data  <- read.csv("www/data/hotspot_yearly_data.csv")
head(hotspot_yearly_data, n= 2)
#>   source jurisdiction                region sample_type     onset organism
#> 1  Human          FNQ Cairns and Hinterland         All Community  E. coli
#> 2  Human          FNQ Cairns and Hinterland         All Community  E. coli
#>   antimicrobial year age_group  sex percent_resistant_yearly_overall
#> 1      Amikacin 2008   Overall Both                                0
#> 2      Amikacin 2009   Overall Both                                0
#>   percent_susceptible_yearly_overall num_of_tests_yearly_overall
#> 1                                100                         123
#> 2                                100                         106
#>   num_of_resistant_tests_yearly_overall num_of_susceptible_tests_yearly_overall
#> 1                                     0                                     123
#> 2                                     0                                     106


hotspot_yearly_splitage <- read.csv("www/data/hotspot_yearly_splitage.csv")
# Note: The column "Age" shows age brackets and the column "sex" has the value 'both' for all records
head(hotspot_yearly_splitage, n= 2)
#>   source jurisdiction                region sample_type     onset organism
#> 1  Human          FNQ Cairns and Hinterland         All Community  E. coli
#> 2  Human          FNQ Cairns and Hinterland         All Community  E. coli
#>   antimicrobial year age_group  sex percent_resistant_yearly_overall
#> 1      Amikacin 2008     16-25 Both                                0
#> 2      Amikacin 2008     26-40 Both                                0
#>   percent_susceptible_yearly_overall num_of_tests_yearly_overall
#> 1                                100                          29
#> 2                                100                          39
#>   num_of_resistant_tests_yearly_overall num_of_susceptible_tests_yearly_overall
#> 1                                     0                                      29
#> 2                                     0                                      39


hotspot_yearly_splitsex <- read.csv("www/data/hotspot_yearly_splitsex.csv")
# Note: The column "Age" shows 'overall' for all records and the column "sex" has the value F for female sex or M for male sex
head(hotspot_yearly_splitsex, n= 2)
#>   source jurisdiction                region sample_type     onset organism
#> 1  Human          FNQ Cairns and Hinterland         All Community  E. coli
#> 2  Human          FNQ Cairns and Hinterland         All Community  E. coli
#>   antimicrobial year age_group sex percent_resistant_yearly_overall
#> 1      Amikacin 2008   Overall   F                                0
#> 2      Amikacin 2009   Overall   F                                0
#>   percent_susceptible_yearly_overall num_of_tests_yearly_overall
#> 1                                100                         110
#> 2                                100                          97
#>   num_of_resistant_tests_yearly_overall num_of_susceptible_tests_yearly_overall
#> 1                                     0                                     110
#> 2                                     0                                      97

The regions that antimicrobial resistance is mapped across are displayed on the map below.

#> OGR data source with driver: ESRI Shapefile 
#> Source: "/Users/alys/Documents/2. RA Hotspots/HOTspots/www/data/Australian_regions/Aus_regions.shp", layer: "Aus_regions"
#> with 316 features
#> It has 4 fields